# 3. Plotting an over-dense, short-duration `Spectrogram`

¶

The normal `spectrogram`

method uses non-overlapping intervals
to calculate discrete PSDs for each stride. This is fine for long-duration
data, but give poor resolution when studying short-duration phenomena.

The `spectrogram2`

method allows for highly-overlapping FFT
calculations to over-sample the frequency content of the input `TimeSeries`

to produce a much more feature-rich output.

To demonstrate this, we can download some data associated with the gravitational-wave event GW510914:

```
from gwpy.timeseries import TimeSeries
lho = TimeSeries.fetch_open_data('H1', 1126259458, 1126259467, verbose=True)
```

and can `highpass()`

and `whiten()`

the remove low-frequency noise and try and enhance low-amplitude signals
across the middle of the frequency band:

```
hp = lho.highpass(20)
white = hp.whiten(4, 2).crop(1126259460, 1126259465)
```

Note

We chose to `crop()`

out the leading and trailing 2
seconds of the the whitened data series here to remove any filtering
artefacts that may have been introduced.

Now we can call the `spectrogram2`

method of `gwdata`

to
calculate our over-dense `Spectrogram`

, using a
1/16-second FFT length and high overlap:

```
specgram = white.spectrogram2(fftlength=1/16., overlap=15/256.) ** (1/2.)
specgram = specgram.crop_frequencies(20) # drop everything below highpass
```

Finally, we make a plot:

```
plot = specgram.plot(norm='log', cmap='viridis', yscale='log')
ax = plot.gca()
ax.set_title('LIGO-Hanford strain data around GW150914')
ax.set_xlim(1126259462, 1126259463)
ax.colorbar(label=r'Strain ASD [1/$\sqrt{\mathrm{Hz}}$]')
plot.show()
```

(`png`

)

Here we can see the trace of a high-mass binary black hole system, referred to as GW150914. For more details on this signal, please see Abbott et al. (2016) (the joint LSC-Virgo publication announcing this detection).